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Combining Speed and Accuracy to Assess Error-Free Cognitive Processes

Published online by Cambridge University Press:  01 January 2025

Mark E. Glickman ,
Jeremy R. Gray  and
Carlos J. Morales
Mark E. Glickman*
Affiliation:
Boston University School of Public Health
Jeremy R. Gray
Affiliation:
Yale University
Carlos J. Morales
Affiliation:
Worcester Polytechnic Institute
*
Requests for reprints should be sent to Mark E. Glickman, Center for Health Quality, Outcomes & Economics Research, Edith Nourse Rogers Memorial Hospital (152), Bldg 70, 200 Springs Road, Bedford, MA 01730, USA. E-mail: mg@bu.edu
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Abstract

Both the speed and accuracy of responding are important measures of performance. A well-known interpretive difficulty is that participants may differ in their strategy, trading speed for accuracy, with no change in underlying competence. Another difficulty arises when participants respond slowly and inaccurately (rather than quickly but inaccurately), e.g., due to a lapse of attention. We introduce an approach that combines response time and accuracy information and addresses both situations. The modeling framework assumes two latent competing processes. The first, the error-free process, always produces correct responses. The second, the guessing process, results in all observed errors and some of the correct responses (but does so via non-specific processes, e.g., guessing in compliance with instructions to respond on each trial). Inferential summaries of the speed of the error-free process provide a principled assessment of cognitive performance reducing the influences of both fast and slow guesses. Likelihood analysis is discussed for the basic model and extensions. The approach is applied to a data set on response times in a working memory test.

Keywords

competing risksreaction timesspeed/accuracy tradeofftime-to-event modelworking memory tasks
Type
Original Paper
Information
Psychometrika , Volume 70 , Issue 3 , September 2005 , pp. 405 - 425
Copyright
Copyright © 2005 The Psychometric Society

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Footnotes

The authors wish to thank Roger Ratcliff, Christopher Chabris, and three anonymous referees for their helpful comments, and Aureliu Lavric for providing the data analyzed in this paper.

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